Open-source, high-throughput targeted in situ transcriptomics for developmental and tissue biology

Author:

Lee Hower1ORCID,Langseth Christoffer Mattsson1ORCID,Salas Sergio Marco1ORCID,Sariyar Sanem2ORCID,Metousis Andreas1ORCID,Rueda-Alaña Eneritz34ORCID,Bekiari Christina1ORCID,Lundberg Emma256ORCID,Garcı́a-Moreno Fernando347ORCID,Grillo Marco1ORCID,Nilsson Mats1ORCID

Affiliation:

1. Stockholm University 1 Science for Life Laboratory, Department of Biochemistry and Biophysics , , 171 65 Solna , Sweden

2. KTH - Royal Institute of Technology, 17165 2 Science for Life Laboratory, Department of Protein Science , Stockholm , Sweden

3. Achucarro Basque Center for Neuroscience, Scientific Park of the University of the Basque Country (UPV/EHU) 3 , 48940 Leioa , Spain

4. Faculty of Medicine and Odontology, UPV/EHU, Barrio Sarriena s/n 4 Department of Neuroscience , , 48940 Leioa, Bizkaia , Spain

5. Stanford University 6 Department of Bioengineering , , Stanford, CA 94305 , USA

6. Stanford University 7 Department of Pathology , , Stanford, CA 94305 , USA

7. IKERBASQUE Foundation, María Díaz de Haro 3 5 , 6th Floor, 48013 Bilbao Spain

Abstract

ABSTRACT Multiplexed spatial profiling of mRNAs has recently gained traction as a tool to explore the cellular diversity and the architecture of tissues. We propose a sensitive, open-source, simple and flexible method for the generation of in situ expression maps of hundreds of genes. We use direct ligation of padlock probes on mRNAs, coupled with rolling circle amplification and hybridization-based in situ combinatorial barcoding, to achieve high detection efficiency, high-throughput and large multiplexing. We validate the method across a number of species and show its use in combination with orthogonal methods such as antibody staining, highlighting its potential value for developmental and tissue biology studies. Finally, we provide an end-to-end computational workflow that covers the steps of probe design, image processing, data extraction, cell segmentation, clustering and annotation of cell types. By enabling easier access to high-throughput spatially resolved transcriptomics, we hope to encourage a diversity of applications and the exploration of a wide range of biological questions.

Funder

Chan Zuckerberg Initiative

Silicon Valley Community Foundation

Erling-Perssons Stiftelse

Knut och Alice Wallenbergs Stiftelse

Vetenskapsrådet

Cancerfonden

Eusko Jaurlaritza

Ikerbasque, Basque Foundation for Science

Ministerio de Ciencia e Innovación

European Advanced infraStructure for Innovative Genomics

Stockholms Universitet

Publisher

The Company of Biologists

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